R: Benchmark experiment for multiple learners and tasks.

benchmark {mlr}

R Documentation

Benchmark experiment for multiple learners and tasks.

Description

Complete benchmark experiment to compare different learning algorithms across one or more tasks w.r.t. a given resampling strategy. Experiments are paired, meaning always the same training / test sets are used for the different learners. Furthermore, you can of course pass “enhanced” learners via wrappers, e.g., a learner can be automatically tuned using makeTuneWrapper.

Usage

benchmark(learners, tasks, resamplings, measures, keep.pred = TRUE,
  keep.extract = FALSE, models = FALSE,
  show.info = getMlrOption("show.info"))

Arguments

`learners`	(list of Learner \| character) Learning algorithms which should be compared, can also be a single learner. If you pass strings the learners will be created via makeLearner.
`tasks`	list of Task Tasks that learners should be run on.
`resamplings`	(list of ResampleDesc \| ResampleInstance) Resampling strategy for each tasks. If only one is provided, it will be replicated to match the number of tasks. If missing, a 10-fold cross validation is used.
`measures`	(list of Measure) Performance measures for all tasks. If missing, the default measure of the first task is used.
`keep.pred`	(`logical(1)`) Keep the prediction data in the `pred` slot of the result object. If you do many experiments (on larger data sets) these objects might unnecessarily increase object size / mem usage, if you do not really need them. The default is set to `TRUE`.
`keep.extract`	(`logical(1)`) Keep the `extract` slot of the result object. When creating a lot of benchmark results with extensive tuning, the resulting R objects can become very large in size. That is why the tuning results stored in the `extract` slot are removed by default (`keep.extract = FALSE`). Note that when `keep.extract = FALSE` you will not be able to conduct analysis in the tuning results.
`models`	(`logical(1)`) Should all fitted models be stored in the ResampleResult? Default is `FALSE`.
`show.info`	(`logical(1)`) Print verbose output on console? Default is set via configureMlr.

Value

BenchmarkResult.

Examples

lrns = list(makeLearner("classif.lda"), makeLearner("classif.rpart"))
tasks = list(iris.task, sonar.task)
rdesc = makeResampleDesc("CV", iters = 2L)
meas = list(acc, ber)
bmr = benchmark(lrns, tasks, rdesc, measures = meas)
rmat = convertBMRToRankMatrix(bmr)
print(rmat)
plotBMRSummary(bmr)
plotBMRBoxplots(bmr, ber, style = "violin")
plotBMRRanksAsBarChart(bmr, pos = "stack")
friedmanTestBMR(bmr)
friedmanPostHocTestBMR(bmr, p.value = 0.05)